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The goal of this project is to enhance the livability of urban communities by mitigating urban congestion, as well as their sustainability by reducing city-wide energy consumption. The approach of this project is to develop simulation-based optimization (SO) techniques that identify multi-modal urban mobility strategies, which improve traditional congestion metrics (e.g. trip travel times, link densities), while also reducing energy consumption at the urban scale. This project embeds state-of-the-art multi-modal microscopic traffic simulators within novel SO techniques. These SO techniques are then used to address transit signal priority (TSP) problems for congested urban networks. Firstly, the project addresses traditional TSP problem. Secondly, the project integrates the traffic simulator with mode- and vehicle-specific energy consumption simulators. The integrated model is then used to address an energy-efficient TSP problem, where the derived signal plans improve both travel times and city-wide energy consumption patterns. By operating the transportation system in a more integrated manner, e.g. by accounting for multi-modal synergies and interactions, the project can enhance the use of the existing transportation infrastructure as well as the travel experience of its users.